Here’s Why You Shouldn’t Check Your Portfolio Right Now

Market downdrafts tempt people to adjust their investments, but that’s not always a wise choice

If you logged on to your brokerage account today and wish you hadn’t, you’re not alone.

BlackRock Chief Executive Larry Fink said Monday the asset manager hasn’t received this many client calls since March 2020, when the pandemic was beginning.

Retail brokerages including Fidelity Investments had technical glitches Monday morning as traffic surged from people trying to check their portfolios and place trades.

Studies have found that the more people look at their 401(k)s, the lower their long-term returns are likely to be.

The S&P 500 drops on almost half of trading days, so checking your portfolio more often means you are more likely to see losses. And there have been lots of losses since President Trump rolled out a series of tariffs last week.

In just two trading days last week, the average 401(k) lost 7% of its value, according to Alight Solutions , which tracks employer retirement plans. Individual investors moved money out of stock-heavy target-date funds and into the relative safety of bonds and cash.

That’s understandable, but not necessarily wise. Here are some things financial advisers say to keep in mind right now:

Be realistic

Now that the S&P 500 is down almost 20% from its peak, many people are realizing that their risk tolerance isn’t as high as they thought it was when markets were up 20%, said Chelsea Ransom-Cooper, chief financial planning officer at Zenith Wealth Partners in New York.

“It’s a great time to level-set and reflect on what you’re comfortable with,” she said. However, if you decide to make changes, you should tweak a little at a time to avoid making emotional decisions you regret later, she said.

Sell strategically

In general, you should avoid the impulse to sell when the value of your investments falls, said Martin Lowenthal, financial adviser in Needham, Mass.

He has been telling his clients to stay the course and advising that they pull money from alternative sources such as life insurance plans if they need liquidity in the short-term.

“You shouldn’t be drawing from depressed assets if you have other places to go for income,” he said.

However, falling stock prices can create opportunities to save on taxes. If you find yourself with stocks or funds that are worth less than what you paid for them, you may be able to recognize the losses for tax purposes. Selling at a loss and reinvesting the money can help offset taxes on future capital gains while remaining invested in the market.

Buy cautiously

There may be reasons to add to investments, financial advisers say, especially if you have been sitting on cash. Cash losses value to inflation, which is expected to rise as companies digest new tariffs.

With markets starting to price in rate cuts , now might be a good time to lock in returns with fixed-rate products such as certificates of deposits or bonds, Ransom-Cooper said.

If you are younger and have a longer investment horizon, you can consider making small investments into the stock market at regular time intervals to take advantage of a potential rebound while managing risk.

“If you are concerned about inflation, you want to make sure that your money is at least trying to keep up,” she said.

Do nothing

This isn’t the first time the market has tested investors’ stomach for risk, and history says it won’t be the last. There was the financial crisis, then there was the pandemic, and “this time, it’s the tariff tantrum,” Lowenthal said.

“I’ve got full faith in the American economy to ride this out,” he said.

A sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.

The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.

The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.

The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.

This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.

The debt behind the AI build-out

Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.

Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.

JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.

The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.

That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.

A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.

When interest rates rise, those assumptions become less forgiving.

Inflation changes the calculation

September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.

The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.

CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.

Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.

Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.

The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.

China adds another source of pressure

Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.

Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.

The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.

That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.

A reset rather than the end of the boom

The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.

What has changed is the market’s willingness to overlook the price and financing structure of that growth.

The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.

More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.

For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.

Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.

The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.

Fact box

Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026

Philadelphia Semiconductor Index: Down approximately 11.4 per cent

Micron Technology: Down approximately 14.6 per cent

Samsung Electronics: Down approximately 18 per cent

SK Hynix: Down approximately 24 per cent

US September inflation: 3.7 per cent annually

Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion